AI Medical Compendium Topic:
Prostatic Neoplasms

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Optimization based trajectory planning for real-time 6DoF robotic patient motion compensation systems.

PloS one
PURPOSE: Robotic stabilization of a therapeutic radiation beam with respect to a dynamically moving tumor target can be accomplished either by moving the radiation source, the patient, or both. As the treatment beam is on during this process, the pri...

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

La Radiologia medica
OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate canc...

Focusing aptamer selection on the glycan structure of prostate-specific antigen: Toward more specific detection of prostate cancer.

Biosensors & bioelectronics
The development of chemical sensors capable of detecting the specific glycosylation patterns of proteins offers a powerful mean for the early detection of cancer. Unfortunately, this strategy is scarcely explored because receptors recognizing the gly...

Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for...

An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Digital rectal examination (DRE) is considered a quality metric for prostate cancer care. However, much of the DRE related rich information is documented as free-text in clinical narratives. Therefore, we aimed to develop a natural language processin...

Combined Low Dose Rate Brachytherapy and External Beam Radiation Therapy for Intermediate-Risk Prostate Cancer.

Journal of medical imaging and radiation sciences
INTRODUCTION: This is a retrospective study conducted to report the tumor control and late toxicity outcomes of patients with intermediate-risk prostate cancer undergoing combination external beam radiation therapy and low dose rate brachytherapy (LD...

LogLoss-BERAF: An ensemble-based machine learning model for constructing highly accurate diagnostic sets of methylation sites accounting for heterogeneity in prostate cancer.

PloS one
Although modern methods of whole genome DNA methylation analysis have a wide range of applications, they are not suitable for clinical diagnostics due to their high cost and complexity and due to the large amount of sample DNA required for the analys...

Learning deep similarity metric for 3D MR-TRUS image registration.

International journal of computer assisted radiology and surgery
PURPOSE: The fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images for guiding targeted prostate biopsy has significantly improved the biopsy yield of aggressive cancers. A key component of MR-TRUS fusion is image registration. H...

A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning.

Medical image analysis
Computer aided diagnosis (CAD) tools help radiologists to reduce diagnostic errors such as missing tumors and misdiagnosis. Vision researchers have been analyzing behaviors of radiologists during screening to understand how and why they miss tumors o...